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Reseach Article

Fuzzy Edge Linking Process on Fuzzy Noise Filtered Image

by G. Sudhavani, S. Sravani, P. Venkateswara Rao, K. Satya Prasad
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Number 15
Year of Publication: 2014
Authors: G. Sudhavani, S. Sravani, P. Venkateswara Rao, K. Satya Prasad
10.5120/16295-6173

G. Sudhavani, S. Sravani, P. Venkateswara Rao, K. Satya Prasad . Fuzzy Edge Linking Process on Fuzzy Noise Filtered Image. International Journal of Computer Applications. 93, 15 ( May 2014), 33-40. DOI=10.5120/16295-6173

@article{ 10.5120/16295-6173,
author = { G. Sudhavani, S. Sravani, P. Venkateswara Rao, K. Satya Prasad },
title = { Fuzzy Edge Linking Process on Fuzzy Noise Filtered Image },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 93 },
number = { 15 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 33-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume93/number15/16295-6173/ },
doi = { 10.5120/16295-6173 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:16:11.647920+05:30
%A G. Sudhavani
%A S. Sravani
%A P. Venkateswara Rao
%A K. Satya Prasad
%T Fuzzy Edge Linking Process on Fuzzy Noise Filtered Image
%J International Journal of Computer Applications
%@ 0975-8887
%V 93
%N 15
%P 33-40
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Processing of images plays a vital role in many fields such as medical and scientific applications. During the transmission of images, effect of noise plays a key role. A fuzzy filter is presented for additive noise removal from color images. During the process of noise removal, some of the edges may be disappeared. This paper presents two independent fuzzy based edge linking algorithms which are capable of finding a set of edge points in an image and linking these edge points by thresholding. The first algorithm includes a set of 16 fuzzy templates, representing the edge profiles of different types. The second algorithm relies on the image gradient to locate breaks in uniform regions and is based on fuzzy if-then rules. Performance evaluation of these algorithms is known by calculating peak signal to noise ratio (PSNR).

References
  1. E. E. Kerre, Fuzzy sets and Approximate Reasoning, Xian, China: Xian Jiaotong Univ. Press, 1998.
  2. Farzam Farbiz, Mohammad Bager Menhaz, Seyed A. Motamedi, and Martin T. Hagan "A New Fuzzy Logic Filter for Image Enhancement" IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS – PART B: CYBERNETICS, VOL. 30, NO. 1, FEBRUARY 2000.
  3. How – Lung Eng, Student Member, IEEE, and Kai-Kuang Ma "Noise Adaptive Soft-Switching Median Filter" IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 10, NO. 2, FEBRUARY 2001.
  4. Dimitri Van De Ville, Mike Nachtegael, Dietrich Van der Weken, Etienne E. Kerre, Wilfried Philipsand Ignace Lemahieu "Noise Reduction by Fuzzy Image Filtering" IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 11, NO. 4, AUGUST 2003.
  5. Stefan Schulte, Valerie De Witte, Mike Nachtegael, Dietrich Van der Weken, and Etienne E. Kerre "Fuzzy Two-Step Filter for Impulse Noise Reduction From Color Images" IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 15, NO. 11, NOVEMBER 2006.
  6. Stefan Schulte, Mike Nachtegael, Valerie De Witte, Dietrich Van der Weken, and Etienne E. Kerre "A Fuzzy Impulse Noise Detection and Reduction Method" IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 15, NO. 5, MAY 2006.
  7. Stefan Schulte "Fuzzy and Nonlinear Restoration and Analysis Techniques for Digital Images".
  8. Tom Melange, Mike Nachtegael, and Etienne E. Kerre "Fuzzy Random Impulse Noise Removal from Color Image Sequences" IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 20, NO. 4, APRIL 2011.
  9. G. Sudhavani and K. Satya Prasad "Segmentation of Lip Images by Modified Fuzzy C- means Clustering Algorithm" International Journal of Computer Science & Network Security, Vol. 9 No. 4, April 2009.
  10. "FUZZY MODELS AND ALGORITHMS FOR PATTERN RECOGNITION AND IMAGE PROCESSING" by James C. Bezdek, James Keller, Raghu Krisnapuram, Nikhil R. Pal.
  11. T. Chaira, Image Segmentation and Color Retrieval-A Fuzzy and Intuitionistic Fuzzy Set Theoretic Approach, PhD Thesis, Indian Institute of Technology, Kharagpur. India, 2004.
  12. T. Chaira, A. K. Ray, Segmentation using fuzzy divergence, Pattern Recog. Lett. 24 (12) (2003) 1837-1844.
  13. C. Vertan and V. Buzuloiu, "Fuzzy nonlinear filtering of color images," in Fuzzy Techniques in Image Processing, E. E. Kerre and M. Nachtegael, Eds. , 1st ed. Heidelverg, Germany: Physica Verlag, 2000, vol. 52, pp. 248-264.
  14. S. M. Guo, C. S. Lee, and C. Y. Hsu, "An intelligent image agent based on soft-computing techniques for color image processing," Expert Sist Appl. , vol. 28, pp. 483-494, Apr. 2005.
  15. T. Takagi and M. Suguno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. Syst. , Man, Cybern. , vol. SMC-15, no. 1, pp. 116-132, Jan. 1985.
  16. G. Sudhavani, G. Madhuri, P. Venkateswa Rao & K. Satya Prasad "Removing Gaussian Noise from Color Images by Varying the Size of Fuzzy Filters" International Journal of Computer Applications (0975 – 8887), Vol. 72, No. 17, June 2013.
  17. K. T. Atanassov, Intuitionistic fuzzy set. Fuzzy Sets Syst. (1986) 87-97.
  18. "Computational Intelligence in Medical Informatics" by Arpad Kelemen, Ajith Abraham . Yulan Liang (Eds. )
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy filter Fuzzy rule - based system Additive noise Gradient Edge detection Intuitionistic fuzzy set Membership degree Hesitation degree Intuitionistic fuzzy divergence Fuzzy interference system.